Minimum variance hedging with bivariate regime-switching model for WTI crude oil

Energy

Volumn 36, Issue 5, 2011, Pages 3050-3057

  Hung, Jui Cheng ^a   Wang, Yi Hsien ^a   Chang, Matthew C ^b   Shih, Kuang Hsun ^a   Kao, Hsiu Hsueh ^c  

^a CHINESE CULTURE UNIVERSITY   (Taiwan)

^b HSUAN CHUANG UNIVERSITY   (Taiwan)

^c TAMKANG UNIVERSITY   (Taiwan)

Author keywords

Four regime bivariate Markov switching model; In and out of sample hedging performances; SPA test; TVC GARCH

Indexed keywords

CRUDE OIL; OPTIMIZATION;

BIVARIATE; EMPIRICAL RESULTS; HEDGE RATIO; IN- AND OUT-OF-SAMPLE HEDGING PERFORMANCES; MARKOV SWITCHING MODELS; MINIMUM VARIANCE; REGIME-SWITCHING MODELS; SPA TEST; TIME VARYING; TVC-GARCH; TWO-REGIME; WEST TEXAS INTERMEDIATES;

SWITCHING;

CRUDE OIL; EMPIRICAL ANALYSIS; NUMERICAL MODEL; SAMPLING;

EID: 79955654563     PISSN: 03605442     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.energy.2011.02.049     Document Type: Article

References (38)

1. Agnolucci P. Volatility in crude oil futures: a comparison of the predictive ability of GARCH and implied volatility models. Energy Economics 2009, 31:316-321.
2. Alizadeh A., Nomikos N.A. Markov regime switching approach for hedging stock indices. Journal of Futures Markets 2004, 24(7):649-657.
3. Bollen N.P.B., Gray S.F., Robert E.W. Regime switching in foreign exchange rates: evidence from currency option prices. Journal of Econometrics 2000, 94:239-276.
4. Bollerslev T., Wooldridge J.M. Quasi-maximum likelihood estimation and inference in dynamic models with time varying covariances. Econometric Review 1992, 11:143-172.
5. Byström H.N.E. The hedging performance of electricity futures on Nordic power exchange. Applied Economics 2003, 35:1-11.
6. Engle R.F. Dynamic conditional correlation: a new simple class of multivariate GARCH models. Journal of Business and Economic Statistics 2002, 20:339-350.
7. Fong W.M., See Kh A Markov switching model of the conditional volatility of crude oil futures. Energy Economics 2002, 24:71-95.
8. Ferderer J. Oil price volatility and the macroeconomy. Journal of Macroeconomics 1996, 18(1):1-26.
9. Giot P., Laurent S. Market risk in commodity markets: a VaR approach. Energy Economics 2003, 25:435-457.
10. Gray S.F. Modeling the conditional distribution of interest rates as a regime-switching process. Journal of Financial Economics 1996, 42:27-62.
11. Hamilton J.D. A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 1989, 57:357-384.
12. Hamilton J.D. Rational expectations econometric analysis of changes in regime: an investigation of the term structure of interest rates. Journal of Economic Dynamics and Control 1988, 12:385-423.
13. Hamilton J.D., Susmel R. Autoregressive conditional heteroskedasticity and changes in regime. Journal of Econometrics 1994, 64:307-333.
14. Hansen P.R. A test for superior predictive ability. Journal of Business and Economic Statistics 2005, 23(4):365-380.
15. Hansen P.R., Lunde A. A forecast comparison of volatility models: does anything beat a GARCH(1,1)?. Journal of Applied Econometrics 2005, 20(7):873-889.
16. Hsu Ku Y.H. Student-t distribution based VAR-MGARCH: an application of the DCC model on international portfolio risk management. Applied Economics 2008, 40:1685-1697.
17. Hsu C.C., Tseng C.P., Wang Y.H. Dynamic hedging with futures: a coula-based GARCH model. Journal of Futures Markets 2008, 28(11):1095-1116.
18. Huang R.D., Masulis R.W., Stoll H.R. Energy shocks and financial markets. Journal of Futures Markets 1996, 16(1):1-27.
19. Jarque C.M., Bera A.K. A test for normality of observations and regression residuals. International Statistical Review 1987, 55:163-172.
20. Ljung G.M., Box G.E.P. On a measure of lack of fit in time series models. Biometrika 1978, 65:297-303.
21. Kang S.H., Kang S.M., Yoon S.M. Forecasting volatility of crude oil markets. Energy Economics 2009, 31:119-125.
22. Kroner K.F., Sultan J. Time-varying distribution and dynamic hedging with foreign currency futures. Journal of Financial and Quantitative Analysis 1993, 28:535-551.
23. Lee K., Ni S., Ratti R.A. Oil shocks and the macroeconomy: the role of price variability. The Energy Journal 1995, 16(4):39-56.
24. Lien D., Yang L. Asymmetric effect of basis on dynamic futures hedging: empirical evidence from commodity markets. Journal of Banking and Finance 2008, 32:187-198.
25. Lee H.T., Yoder J.K. A bivariate markov regime switching GARCH approach to estimate time varying minimum variance hedge ratios. Applied Economics 2007, 39:1253-1265.
26. Lee H.T., Yoder J.K. Optimal hedging with a regime-switching time-varying correlation GARCH model. Journal of Futures Markets 2007, 27(5):495-516.
27. Lee H.T. Optimal futures hedging under jump switching dynamics. Journal of Empirical Finance 2009, 16:446-456.
28. Lee H.T., Yoder J.K., Mittelhammer R.C., McCluskey J.J. A random coefficient autoregressive Markov regime switching model for dynamic futures hedging. Journal of Futures Markets 2006, 26(2):103-129.
29. Mount T.D., Ning Y., Cai X. Predicting price spikes in electricity markets using a regime-switching model with time-varying parameters. Energy Economics 2006, 28:62-80.
30. Park T.H., Switzer L.N. Bivariate GARCH estimation of the optimal hedge ratios for the stock index futures. Journal of Futures Markets 1995, 15:61-67.
31. Politis D.N., Romano J.P. The stationary bootstrap. Journal of the American Statistical Association 1994, 89:1303-1313.
32. Regnier E. Oil and energy price volatility. Energy Economics 2007, 29:405-427.
33. Sadorsky P. Oil price shocks and stock market activity. Energy Economics 1999, 21(5):449-469.
34. Sadorsky P. The macroeconomic determinants of technology stock price volatility. Review of Financial Economics 2003, 12:191-205.
35. Sadorsky P. Modeling and forecasting petroleum futures volatility. Energy Economics 2006, 28:467-488.
36. Sadeghi M., Shavvalpour S. Energy risk management and value at risk modeling. Energy Policy 2006, 34:3367-3373.
37. Tse Y.K., Tsui A.K.C. A multivariate generalized autoregressive conditional heteroscedasticity model with time-varying correlations. Journal of Business and Economic Statistics 2002, 20:351-362.
38. White H. A reality check for data snooping. Econometrica 2000, 68(5):1097-1126.